Azure Cost Visibility Framework for Clients | Technology & AI bringing to light

In today’s cloud-driven world, achieving clear cost visibility is essential for organisations.

Once systems and applications are migrated to the cloud, the need for diligent cost management becomes apparent since expenses are based on a pay-as-you-go (PAYG) model. This means that:

Over-provisioning can lead to excessive costs. It won’t be long before your finance team questions your spending habits.
If you under-provision, your applications’ performance may decline, risking your organisation’s reputation both internally and externally.

This underscores the necessity of selecting the right services with the appropriate SKUs to manage costs effectively. This is the essence of FinOps — equipping knowledgeable engineers with the tools and dashboards they need to monitor the efficient use of cloud resources.

Moreover, having adequate tools and expertise is not enough; comprehensive cost visibility is critical. Without it, prioritising areas for improvement in your FinOps optimisation efforts becomes challenging. Understanding where most of your expenses lie is fundamental to these initiatives.

As a Managed Service Provider (MSP), our role is to help clients achieve this visibility, resulting in enhanced cost control. Once this visibility is secured, what I term the ‘Prius effect’ occurs — an immediate rise in cost accountability and awareness throughout the organisation. Real-time spending insights empower organisations to accelerate investments (‘press the gas pedal’) or curtail expenses (‘step on the brakes’) based on immediate needs.

What Is a Cost Visibility Framework?

A Cost Visibility Framework is crucial for helping clients maintain control over cloud expenditure.

We believe it should incorporate several key elements:

Detailed cost visibility across various tenants and cloud platforms
A robust tagging strategy for accurate cost allocation and accountability
Proactive, rather than reactive, cost monitoring and alerting
Cost forecasting and estimation capabilities

Step 1: Standardise Cost Tagging Across Clients

Effective cost tagging is the cornerstone of any solid visibility framework. Accurate tags enable precise cost allocation and a clearer understanding of spending behaviours.

Cost allocation is vital in every organisation:

In larger organisations, it underpins two important processes: Chargeback and Showback. These are essential when managing cloud contracts and licences centrally, enabling a financial mechanism to charge (Chargeback) or report (Showback) costs to various departments.
Smaller organisations also benefit from it—if not for chargeback or showback, then simply to assess the expenses linked to specific applications or projects. This insight is crucial for evaluating the value against the costs of cloud workloads.

Tags can also delineate resource ownership, so I recommend including owner-type tags that identify the Business Owner for specific resources, fostering accountability.

Standardised tagging across all clients also simplifies the onboarding process for new consultants, making intricate setups more manageable.

Essential Tags for Azure Resources:

Environment: prod/dev/pre/uat/tst
Department/Business Unit: Finance, Marketing, Engineering, Operations
Project/Application: Application identifier following the organisation’s naming convention
Owner: Responsible technical team
Cost Center: For financial allocation and chargeback
Criticality: Critical, High, Medium, Low

Implementation Strategy:

Establish a company-wide tagging policy that all teams must adhere to. Communication is critical at this juncture, so it’s necessary to convey the benefits of this tagging strategy for securing team buy-in.
Utilise Azure Policy to enforce mandatory tags and restrict resource creation without appropriate tagging.
Implement tag inheritance, so child resources automatically inherit tags from parent resources.
Conduct regular audits to ensure tagging compliance and rectify any inconsistencies.
Employ automation tools to apply tags retroactively to existing resources through Infrastructure-as-Code, scripting, or other means, tailored to the organisation.

Best Practices:

Maintain consistent tag names and standardised values.
Limit required tags to streamline the process. Simplicity and manageability in tagging are crucial.
Document the tagging strategy and train teams on effective usage.
Leverage Azure Resource Graph/Azure Log Analytics Workbooks to query and check tag compliance.
Use Azure Policy for automated tag inheritance and stringent tag enforcement.
Apply tags efficiently using Infrastructure-as-Code (Terraform, Bicep, ARM, etc.).

Step 2: Centralise Multi-Tenant or Multi-Cloud Cost Data

Effectively managing expenses across various Azure tenants or cloud providers necessitates centralised visibility to avoid blind spots and facilitate comprehensive cost analyses. Multi-tenant environments pose challenges such as fragmented cost data across subscriptions and tenants and difficulties in aggregating costs for organisation-wide insights.

To address these issues, Azure offers several solutions. The Azure Cost Management API allows for programmatic extraction of cost data from multiple tenants via REST APIs. Management Groups can help organise subscriptions under a central governance framework. For MSPs overseeing multiple tenant clients, Azure Lighthouse offers cross-tenant management capabilities. Furthermore, Cost Management Cost Exports can be set up on each subscription to consolidate billing data into a single Azure Storage Account or Data Lake, enabling the rapid development of reusable Power BI dashboards across multiple clients.

In multi-cloud environments, leveraging cloud-agnostic cost management tools that accommodate Azure, AWS, and GCP is essential. The FOCUS standard simplifies the normalisation of cost data formats across various cloud platforms and is supported by all major providers. Consistency in tagging across all platforms is vital for unified cost management.

Step 3: Define Cost Allocation and Accountability Rules

Certain cost allocation rules guarantee that expenses are correctly assigned to the right teams or projects, enabling accurate chargeback and showback reports.

Cost Allocation Models:

Direct Allocation: Costs linked directly to specific resources or projects.
Proportional Allocation: Shared costs divided based on usage percentages.
Fixed Allocation: Shared infrastructure costs allocated equally among users.
Activity-Based Allocation: Costs distributed according to actual usage metrics.

A good starting point for cost allocation is to organize subscriptions and resource groups effectively. If an organisation is structured into several business units, consider assigning one subscription per unit, while having one or more subscriptions dedicated to shared services.

This method allows for clear attribution of costs associated with each business unit based on:

Their respective subscriptions.
The expenses linked to shared subscriptions. Begin with simpler allocation methods (proportional allocation based on estimated usage) and work up to more sophisticated models, adhering to the FinOps principle of crawl, walk, run.

Accountability Framework:

Resource Owners: Technical teams responsible for optimising their resources.
Budget Owners: Business units accountable for adhering to their budgets.
FinOps Team: Central team overseeing cost governance and optimisation.
Executive Sponsors: Leadership providing strategic direction and budget approvals.

Implementation Steps:

Map all Azure resources to cost centers or business units.
Establish allocation rules for shared services (networking, security, management).
Set up monthly/quarterly cost review processes.
Create automated reports for showback/chargeback purposes tailored for budget owners.
Implement cost variance alerts to notify when spending deviates from expected patterns using Azure Budgets and Azure Cost Management Anomaly Detection.

Key Metrics to Track:

Cost per business unit or department
Cost per project or application
Cost comparison between production and non-production environments
Allocation of shared services costs
Budget variance analysis

Step 4: Implement Proactive Reporting and Alerts

Reactive approaches to cost management often result in budget overruns and missed optimisation chances. Proactive monitoring allows teams to implement corrective measures before costs escalate.

Organisations should configure various alert types to cover all bases. Budget alerts notify when expenses near or exceed thresholds, typically set at 50% (early warning), 75% (management escalation), and 90% (critical alert requiring urgent action). Anomaly detection flags unusual spending spikes or patterns, such as a daily increase of over 20% compared to the average or weekly trends predicting over 110% of the monthly budget. Resource-specific alerts focus on high-cost resources to identify optimisation opportunities, while trend alerts highlight spending patterns forecasting future budget issues. Idle resource alerts pinpoint unused or underutilised resources.

Reporting should adhere to a fixed schedule: daily reports for anomalies and critical breaches, weekly summaries for spending trends, detailed monthly cost allocation reports with optimisation suggestions, and quarterly strategic reviews and budget sessions.

For automation, utilise Azure Cost Management + Billing alerts for baseline monitoring, tailor Logic Apps or Azure Functions for complex alerts, create automated reports with Power BI or similar tools, and establish Slack or Teams notifications for immediate visibility on alerts.

Step 5: Forecast and Review Periodically

Regular forecasting and reviews are essential to align cost management with business objectives and unveil potential optimisation opportunities. Keep in mind that for accurate forecasting, costs from new projects must be accounted for, and so should those of projects nearing decommissioning.

For new initiatives, costs need to be estimated beforehand and integrated into budgets, while stakeholders must be informed of expected decreases in costs for projects winding down. Both aspects are critical for comprehensive forecasting exercises.

Effective forecasting combines several elements: historical analyses evaluating 3-6 months of data for trend identification, growth projections considering any planned business expansions or new projects, seasonal adjustments reflecting business cycles, and resource planning for upcoming infrastructure changes. Market factors related to changes in cloud provider pricing and new services must also be taken into account.

Organisations should establish a structured review schedule:

Monthly reviews for analysing actual against forecast variances and making short-term adjustments.
Quarterly business reviews to evaluate strategic alignment and reforecast budgets.
Annual planning for long-term capacity and budget allocation.
Ad-hoc reviews triggered by significant changes in business or cost concerns.

During these reviews, teams should analyse cost variance, update resource allocation strategies, prioritise optimisation opportunities, measure the effectiveness of existing cost controls, and plan for upcoming business initiatives and their cost implications.

For effective forecasting tools and methods, organisations can harness native forecasting capabilities in Azure Cost Management, implement predictive analytics via machine learning, utilise simple spreadsheet models for initial scenarios, or deploy advanced forecasting tools through third-party FinOps platforms.

Measure success by evaluating forecast accuracy (aiming for within 5-10% of actual costs), cost savings achieved through optimisation, reductions in budget variances over time, and the timeframe taken to identify and resolve cost issues.

How Turbo360 Facilitates Comprehensive Cost Visibility

Turbo360 offers MSPs an extensive platform to establish a complete cost visibility framework for their Azure clients:

Unified Cost Dashboard:

Consolidate costs across numerous Azure tenants and subscriptions.
Real-time cost monitoring with configurable views.
Ability to delve into data from the organisation level down to individual resources.

Advanced Tagging and Allocation:

Automated monitoring and enforcement of tagging compliance.
Customisable cost allocation rules tailored to business requirements.
Support for intricate multi-tenant cost allocation scenarios.

Proactive Monitoring and Alerts:

AI-driven anomaly detection for identifying unusual spending behaviours.
Flexible alert thresholds and notification channels according to preferences.
Automated recommendations for cost optimisation.

Comprehensive Reporting:

Client-specific branded cost reports for MSP partners.
Automated monthly and quarterly cost review documents.
Dashboards for executives enabling strategic decision-making.

Forecasting and Planning:

Machine learning-driven cost forecasting.
Scenario planning to evaluate impacts of business growth and infrastructure changes.
Integration with budgeting and business planning processes.

Conclusion

Building a robust cost visibility framework is indispensable for MSPs aiming to deliver value to their Azure clients. By implementing standardised tagging, centralising cost data, establishing clear allocation rules, enabling proactive monitoring, and setting regular review cycles, MSPs can assist clients in achieving genuine cost control within the cloud environment. Though this initiative presents challenges, leveraging ready-to-use tools and frameworks can expedite the process, easing the setup with new clients.

The key to long-term success is to perceive cost visibility as a continual discipline rather than a one-off project. Organisations that commit to establishing effective cost visibility frameworks will find themselves in a stronger position to optimise their cloud expenditures, make informed decisions, and enhance their returns on cloud investments.

Remember the ‘Prius effect’ — increased visibility naturally leads to more judicious behaviours. Once your clients can clearly observe their cloud expenditures, they will inevitably become more cost-aware, leading to improved decisions regarding resource usage and optimisation.